Chemical Composition and Antibacterial Activity of Essential Oils of Iranian Herbs Against Staphylococcus Aureus Isolated from Milk

Chemical composition and antibacterial activity of essential oils from three endemic plants including, Thymus daenensis Celak, Dracocephalum multicaule Montbr & Auch., Satureja bachtiarica Bunge and one native plant, Tanacetum polycephalum Schultz-Bip were determined. Volatile oils analyzed using gas chromatography and gas chromatography-mass spectrometry. The in-vitro antibacterial activity was performed by agar disc diffusion and micro-dilution assays. The results revealed distinct differences in the compounds depending on sample plant. Among the plant species screened, essential oils of S. bachtiarica and T. daenensis showed highest antibacterial activity against Staphylococcus aureus.     

Performance evaluation of a routing algorithm based on Hopfield Neural Network for network-on-chip

Network on chip (NoC) has emerged as a solution to overcome the system on chip growing complexity and design challenges. A proper routing algorithm is a key issue of an NoC design. An appropriate routing method balances load across the network channels and keeps path length as short as possible. This survey investigates the performance of a routing algorithm based on Hopfield Neural Network. It is a dynamic programming to provide optimal path and network monitoring in real time. The aim of this article is to analyse the possibility of using a neural network as a router. The algorithm takes into account the path with the lowest delay (cost) form source to destination. In other words, the path a message takes from source to destination depends on network traffic situation at the time and it is the fastest one. The simulation results show that the proposed approach improves average delay, throughput and network congestion efficiently. At the same time, the increase in power consumption is almost negligible.     

Deposition of α-SiΜο12Ο40-[Ru(bipyridine)(terpyridine)Cl] multilayer film on single wall carbon nanotube modified glassy carbon electrode: Improvement of the electrochemical properties and chemical stability

A simple procedure was developed for the preparation of glassy carbon electrodes modified with single wall carbon nanotubes (SWCNTs) and multilayers of SiΜο₁₂Ο₄₀⁴⁻-[Ru(bpy)(tpy)Cl]⁺(byp; bipyridine, tpy; terpyridine). Layer-by-layer deposition technique was used for the multilayer formation of SiΜο₁₂Ο₄₀⁴⁻-[Ru(bpy)(tpy)Cl]⁺ onto SWCNTs films. Based on the strong electrostatic attraction of oppositely charged species a Ru-complex/poly oxometalate hybrid film strongly and irreversibly adsorbed on the glassy carbon electrode modified with single walled carbon nanotubes. The multilayer assembly exhibited good stability and excellent electrochemical reversibility for both redox systems in the pH range1-7. It was found that up to fifteen monolayers could be deposited onto a carbon nanotube film with well defined redox behavior. The modified electrode shows excellent electrocatalytic activity towards sulfite oxidation. Due to synergistic effect between SWCNTs and oppositely charged species the repeated alternate adsorption of anions and cations by this simple dipping method leads to molecular sandwiches with interesting redox activity and remarkable stability.     

Improvement of Nanoscale SOI MOSFET Heating Effects by Vertical Gaussian Drain-Source Doping Region

Silicon - This paper presents an efficient method to improve the heating effects in Nanoscale SOI MOSFET with the Vertical Gaussian Doping Profile in Drain and Source regions (D-S-G-SOI). Three...     

Improvement the Breakdown Voltage and the On-resistance in the LDMOSFET: Double Buried Metal Layers Structure

Silicon - In this paper, a new method is investigated to improve the breakdown voltage in the lateral power MOSFET transistors. The structure is based on Double Buried Metal Layers in the Lateral...     

Characteristics of heat insulating clay bricks made from zeolite,waste steel slag and expanded perlite

In order to lessen the energy loss of buildings during the operation phase, and also considering the importance of sustainable construction, producing bricks having more desirable thermal characteristics has become essential. In this study, insulation bricks composed of expanded perlite (EP), natural zeolite, ground granulated blast furnace slag (GGBFS) and clay were fabricated. The effect of replacing clay with GGBFS, zeolite and EP in amounts up to 15%, 15%, and 50% respectively on the bricks' properties was investigated. Mix proportion parameters of bricks were analyzed using the Taguchi method. Various properties of bricks including density, weight loss, shrinkage, apparent porosity, water absorption, resistance to freezing and thawing, compressive strength, thermal conductivity, and microstructural analysis of fired bricks were examined and compared against standard requirements for bricks. Overall, the results showed that while satisfying the standard requirements, bricks containing the aforementioned additives had lower thermal conductivity compared to normal bricks, and therefore, they could be utilized as heat insulation materials.     

On the modeling of the annual corrosion rate in main cables of suspension bridges using combined soft computing model and a novel nature-inspired algorithm

Neural Computing and Applications - Suspension bridges are critical components of transport infrastructure around the world. Therefore, their operating conditions should be effectively monitored to...     

A 110–140 GHz Millimeter-Wave VCO Using Varactor and Bulk Effective Technique in 65 nm CMOS Process

In this paper, an enhanced voltage controlled oscillator (VCO) at center frequency 125 GHz with tuning rang of 24% is presented. The proposed idea is based on the tuning capacitance using MOS varactor. The structure is consisted of applying an MOS varactor capacitor to the drain and bulk (in parallel) of NMOS transistor in 65 nm CMOS standard technology. The obtained output of the proposed VCO at 2nd harmonic is tunable at 110–140 GHz frequency with applying?±?1.2 input tuning voltage. Simulation results of the proposed circuit are obtained after extracting post layout (with total chip size of 0.07 mm²) and confirm theoretical results. Compared to the resent designs, the obtained results indicate that the proposed circuit has high tuning range, low die area and a good figure of merit @ 1.2 power supply voltage.

     

A Stable Analytical Solution Method for Car-Like Robot Trajectory Tracking and Optimization

In this paper, the car-like robot kinematic model trajectory tracking and control problem is revisited by exploring an optimal analytical solution which guarantees the global exponential stability of the tracking error. The problem is formulated in the form of tracking error optimization in which the quadratic errors of the position, velocity, and acceleration are minimized subject to the rear-wheel car-like robot kinematic model. The input-output linearization technique is employed to transform the nonlinear problem into a linear formulation. By using the variational approach, the analytical solution is obtained, which is guaranteed to be globally exponentially stable and is also appropriate for real-time applications. The simulation results demonstrate the validity of the proposed mechanism in generating an optimal trajectory and control inputs by evaluating the proposed method in an eight-shape tracking scenario.     

A novel hybrid method based on fuzzy cognitive maps and fuzzy clustering algorithms for grading celiac disease

This paper presents a new method based on fuzzy cognitive map (FCM) and possibilistic fuzzy c-means (PFCM) clustering algorithm for categorizing celiac disease (CD). CD is a complex disorder whose development is affected by genetics (HLA alleles) and gluten ingestion. The celiac patients who are not treated are at a high risk of cancer, malignant lymphoma, and small bowel neoplasia. Therefore, CD diagnosis and grading are of paramount importance. The proposed FCM models human thinking for the purpose of classifying patients suffering from CD. We used the latest grading method where three grades A, B1, and B2 are used. To improve FCM efficiency and classification capability, a nonlinear Hebbian learning algorithm is applied for adjusting the FCM weights. To this end, 89 cases are studied. Three experts extracted seven main determinant characteristics of CD which were considered as FCM concepts. The mutual effects of these concepts on one another and on the final concept were expressed in the form of fuzzy rules and linguistic variables. Using the center of gravity defuzzifier, we obtained the numerical values of these weights and obtained the total weight matrix. Ultimately, combining the FCM model with PFCM algorithm, we obtained the grades A, B1, and B2 accuracies as 88, 90, and 91%, respectively. The main advantage of the proposed FCM is the good transparency and interpretability in the decision-making procedure, which make it a suitable tool for daily usage in the clinical practice.